data_laundry – AI Model by faridlazuarda | AlphaNeural AI

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faridlazuarda/
data_laundry

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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data_laundry

This model is a fine-tuned version of on the massive dataset. It achieves the following results on the evaluation set:

Loss: 1.0394
F1: 0.7983

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
5.4021	0.5	719	4.2520	0.1592
3.5936	1.0	1438	3.0222	0.4171
2.6221	1.5	2157	2.2881	0.5433
2.1941	2.0	2876	2.0383	0.6238
1.8688	2.5	3595	1.7730	0.6562
1.7334	3.0	4314	1.6450	0.6885
1.5359	3.5	5033	1.5398	0.7121
1.4867	3.99	5752	1.4296	0.7324
1.353	4.49	6471	1.3721	0.7393
1.3088	4.99	7190	1.3110	0.7530
1.2006	5.49	7909	1.2633	0.7482
1.1845	5.99	8628	1.2417	0.7635
1.111	6.49	9347	1.2015	0.7795
1.0722	6.99	10066	1.1605	0.7813
1.0121	7.49	10785	1.1383	0.7781
1.018	7.99	11504	1.1024	0.7990
0.9202	8.49	12223	1.0905	0.7898
0.9639	8.99	12942	1.0695	0.7967
0.915	9.49	13661	1.0444	0.7935
0.8743	9.99	14380	1.0394	0.7983

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.14.0